Python

Search

keras linear regression

from pylab import *
from keras.models import Sequential
from keras.layers import Dense

#Generate dummy data
data = data = linspace(1,2,100).reshape(-1,1)
y = data*5

#Define the model
def baseline_model():
   model = Sequential()
   model.add(Dense(1, activation = 'linear', input_dim = 1))
   model.compile(optimizer = 'rmsprop', loss = 'mean_squared_error', metrics = ['accuracy'])
   return model


#Use the model
regr = baseline_model()
regr.fit(data,y,epochs =200,batch_size = 32)
plot(data, regr.predict(data), 'b', data,y, 'k.')

Comment

PREVIOUS	NEXT

Code Example
Python :: import local module python
Python :: get mac address python
Python :: python tkinter scrollbar widget
Python :: python wait for x seconds
Python :: qlistwidget item clicked event pyqt
Python :: randomforestregressor in sklearn
Python :: Plot regression line from sklearn
Python :: distplot with plotly
Python :: Read all the lines as a list in a file using the readlines() function
Python :: how to get a number from a string in python
Python :: in pandas how to start an index from a specific number
Python :: pandas replace row values based on condition
Python :: endswith python
Python :: python console width
Python :: keras example
Python :: sqlite query in python
Python :: assign multiple variables in python
Python :: multiple variables in for loop python
Python :: list of numbers
Python :: transpose matrix numpy
Python :: select non nan values python
Python :: python recurrent timer
Python :: hardest python questions
Python :: python replace string
Python :: dataframe add row
Python :: 13 pseudo random numbers between 0 to 3 python
Python :: python nested list comprehension
Python :: python package version
Python :: imread real color cv2
Python :: python ftplib get list of directories

Search

PYTHON

keras linear regression

ADD CONTENT